1. Field of the Invention
The present invention relates to display advertising.
2. Background
Certain display advertisement (“ad”) networks enable display ads to be served to users who visit the Web sites of publishers that are participating in the display ad network. Advertisers generate the display ads and buy placements (a.k.a. inventory) for those ads on the publishers' Web sites usually based on the anticipated audiences for those sites. A placement represents a publisher's agreement to serve a trafficked (i.e., specified) ad to users when the users visit the publisher's site. The publisher often serves the trafficked ad contemporaneously with other content associated with the publisher's site.
Each time an ad is served to a user, an impression is said to occur. Each impression has attribute values that provide information regarding the user to whom the ad is served and/or the Web site with which the impression is associated. When an advertiser considers buying placements for an ad on a publisher's Web site, the advertiser often provides a query to the publisher, requesting a display advertising supply forecast. A display advertising supply forecast is an estimate of a number of impressions, which are to occur in a future time period, that have specified attribute values. The advertiser typically identifies the specified attribute values in the advertiser's query. For instance, the advertiser may want to target users that have certain attributes or Web sites or publishers that have certain attributes.
Theoretically, a publisher can generate a forecast for every possible combination of attribute values for which inventory is available to ensure that a forecast for impressions having attribute values that are specified by an advertiser is available to be provided to the advertiser. However, such a practice may be impractical for a variety of reasons. For example, the number of attributes and values thereof is often substantial. Accordingly, providing a forecast for every possible combination of attribute values may require extensive computations, which may consume substantial bandwidth and/or resources of the publisher. Moreover, the effect of an attribute on a forecast may be dependent on other attributes. For instance, a forecast for which individual effects of respective attributes are combined to provide the forecast may be substantially less accurate than a forecast for which the combination of attributes as a whole is taken into consideration. Furthermore, inventory for many combinations of attribute values may not be significant and/or stable enough to provide a predictable pattern.